Optimization of Cutting Parameters Based on Specific Cutting Energy Consumption for Aluminum 6010 by Using the Analysis of Variance (ANOVA)

2016 ◽  
Vol 842 ◽  
pp. 14-18
Author(s):  
Sri Raharno ◽  
Yatna Yuwana Martawirya ◽  
Heng Rath Visith ◽  
Jeffry Aditya Cipta Wijaya
Keyword(s):  
Energy Consumption ◽  
Analysis Of Variance ◽  
Minimum Energy ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Manufacturing Industries ◽  
Depth Of Cut ◽  
Specific Cutting Energy ◽  
Cutting Energy ◽  
Minimum Energy Consumption

Manufacturing industries have consumed 30% of the total world energy. The main energy source used in those manufacturing industries is the electricity generated from fossil fuels such as oil, gas, and coal as a result in causing the environmental and economic issues. This paper presents an experimental study in order to get the minimum energy consumption during turning of aluminum 6010 with the conventional machine tool under dry cutting condition by optimizing the cutting parameters to contribute to those issues. An analysis of variance (ANOVA) was employed to analyze the effects and contribution of depth of cut, feed, and cutting speed on the response variable, specific cutting energy. The result of this experiment showed that the feed was the most significant factor for minimizing energy consumption followed by the cutting speed and the depth of cut. The minimum energy consumption was obtained when the highest level of cutting parameters have been used.

Optimization of CNC Turning Operations with Multiple Performance Characteristics using Taguchi based Grey Relational Analysis

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
P. Lakshmikanthan ◽  
B. Prabu
Keyword(s):  
Analysis Of Variance ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Turning Operations ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational

This study investigates the optimization of CNC turning operation parameters for Al6061 nickel coated graphite (NCG) metal matrix composite using the Taguchi based grey relational analysis method. The turning operations are carried out with carbide cutting tool inserts. According to the Taguchi quality concept, 3-level orthogonal array was chosen for the experiments. The experiments are conducted at three different cutting speeds (125, 175, 225m/min) with feed rates (0.1, 0.15, 0.2mm/rev) and depth of cut (0.5, 1, 1.5mm) and different % of reinforcement (2.5%, 5%, 7.5%), signal to noise ratio and the analysis of variance are used to optimize cutting parameters. The effects of cutting speed, feed rate and depth of cut on surface roughness and MRR are analyzed. Mathematical models are developed by using the response surface method to formulate the cutting parameters experimental results shown that machining performance can be improved effectively by using this approach, the analysis of variance (ANOVA) is applied to identify the most significant factor for the turning operations according to the weighted sum grade of the GRG. The predict responses shows the models have more than 95% of confident level of R2 value, from the obtained confirmation experiment result, it is observed, there is a good agreement between the estimated value and the experimental value of the grey relational grade. This experimental study reveals that the grey-Taguchi and RSM can be applied successfully for multi response characteristic performances.

scholarly journals Statistical analysis of energy consumption, tool wear and surface roughness in machining of Titanium alloy (Ti-6Al-4V) under dry, wet and cryogenic conditions

2019 ◽  
Vol 10 (2) ◽  
pp. 561-573 ◽  
Author(s):  
Muhammad Ali Khan ◽  
Syed Husain Imran Jaffery ◽  
Mushtaq Khan ◽  
Muhammad Younas ◽  
Shahid Ikramullah Butt ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Effective Means ◽  
Sustainable Manufacturing ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Specific Cutting Energy ◽  
Cutting Energy ◽  
Positive Effect

Abstract. Productivity and economy are key elements of any sustainable manufacturing system. While productivity is associated to quantity and quality, economy focuses on energy efficient processes achieving an overall high output to input ratio. Machining of hard-to-cut materials has always posed a challenge due to increased tool wear and energy loss. Cryogenics have emerged as an effective means to improve sustainability in the recent past. In the present research the use of cooling conditions has been investigated as an input variable to analyze its effect on tool wear, specific cutting energy and surface roughness in combination with other input machining parameters of feed rate, cutting speed and depth of cut. Experimental design was based on Taguchi design of experiment. Analysis of Variance (ANOVA) was carried out to ascertain the contribution ratio of each input. Results showed the positive effect of coolant usage, particularly cryogenic, on process responses. Tool wear was improved by 33 % whereas specific cutting energy and surface roughness were improved by 10 % and 9 % respectively by adapting the optimum machining conditions.

scholarly journals Specific cutting energy consumption in a circular saw for Eucalyptus stands VM01 and MN463

CERNE ◽  
2011 ◽  
Vol 17 (1) ◽  
pp. 109-115 ◽  
Author(s):  
Erica Moraes de Souza ◽  
José Reinaldo Moreira da Silva ◽  
José Tarcísio Lima ◽  
Alfredo Napoli ◽  
Túlio Jardim Raad ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Specific Energy ◽  
Feed Rate ◽  
Specific Energy Consumption ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Specific Cutting Energy ◽  
Cutting Energy ◽  
Circular Saw ◽  
Cutting Speeds

Modern technologies for continuous carbonization of Eucalyptus sp. require special care in wood cutting procedures. Choosing the right tool, cutting speeds and feed rates is important to manage time and energy consumption, both of which being critical factors in optimizing production. The objective of this work is to examine the influence of machining parameters on the specific cutting energy consumption of Eucalyptus sp. stands MN 463 and VM 01, owned by V&M Florestal. Tests were performed at the Wood Machining Laboratory of the Federal University of Lavras (DCF/UFLA). Moist logs 1.70m in length were used. The experiment was set up using a 3 x 3 x 4 x 2 factorial design (cutting speed x feed rate x number of teeth x tree stand). Results were subjected to analysis of variance and means were compared by the Tukey test at the 5% significance level. Greater cutting speeds, lower feed rates and the 40 teeth circular saw consumed more specific energy. Stand MN 463 consumed more specific energy. The combination of cutting speed 46 m.s-1, feed rate 17 m.min-1 and 24 teeth circular saw produced better specific energy consumption results for stand MN 463. As for stand VM 01, the combination of cutting speed 46 m.s-1, feed rate 17 m.min-1 and 20 teeth circular saw resulted in lower specific energy consumption.

Energy conscious cryogenic machining of Ti-6Al-4V titanium alloy

2016 ◽  
Vol 232 (10) ◽  
pp. 1690-1706 ◽  
Author(s):  
Alborz Shokrani ◽  
Vimal Dhokia ◽  
Stephen T Newman
Keyword(s):  
Energy Consumption ◽  
Tool Wear ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cryogenic Cooling ◽  
Depth Of Cut ◽  
Cryogenic Machining ◽  
Coolant Pump ◽  
Cutting Speeds

Manufacturing and, in particular, machining are responsible for a significant portion of global industrial energy consumption (25%). Previous research has shown that precise selection of cutting parameters can improve the energy consumption of machining processes. Cryogenic machining has attracted significant attention for improving the machinability of difficult-to-machine materials while also eliminating the environmental and health issues associated with the use of cutting fluids. Despite the advantages, there is a considerable research gap in cryogenic milling operations. This article investigates the effect of cryogenic cooling using liquid nitrogen in end milling of Ti-6Al-4V. A robust and rigorous methodology was developed and a series of machining experiments were conducted using a combination of cutting parameters repeated at dry, flood and cryogenic cooling environments. The investigations indicated that cryogenic cooling considerably reduce tool wear when compared to dry and flood cooling while allowing for using higher cutting speeds. The cutting tool used for cryogenic machining at 200 m/min cutting speed, 0.03 mm/tooth feed rate and 5 mm depth of cut showed minimum flank wear. Furthermore, the investigations demonstrated that using the machine’s coolant pump in flood cooling resulted in higher power and energy consumption than dry and cryogenic cooling. This article clearly shows that higher material removal rates are required in order to minimise specific machining energy. Therefore, since cutting speed is limited in dry machining, cryogenic machining is the most favourable as higher cutting speeds can be used. Using cryogenic machining at 200 m/min cutting speed resulted in an 88% reduction in energy consumption of the machine tool as compared to flood cooling at 30 m/min while minimum tool wear (10 µm) was detected. This clearly demonstrates the significant capabilities of cryogenic machining when compared with more conventional machining approaches.

Optimization of Cutting Parameters in Turning of AISI 1018 Steel With Constant Material Removal Rate Using Robust Design for Minimizing Cutting Power

2013 ◽  
Author(s):  
C. Camposeco-Negrete ◽  
J. Calderón-Nájera ◽  
J. C. Miranda-Valenzuela
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Robust Design ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimization Of Cutting Parameters

Environmental and energy efficiency awareness of manufacturers and customers along with high electricity costs have promoted the development of strategies to reduce energy consumption in manufacturing processes. Machine tools are one of the main contributors to energy consumption in the industrial sector. Several studies have been undertaken to optimize the cutting parameters in order to minimize the power consumed in the removal of material. However, these studies do not consider the influence that different combinations of cutting parameters can have on power consumption at a constant material removal rate, quantity that has a direct influence in production rates. This paper describes an experimental study of AISI 1018 steel turning under roughing conditions and constant material removal rate, in order to obtain the cutting parameters that minimize power consumption. Robust design is used to analyze the effects of the depth of cut, feed rate and cutting speed on electric power consumed.

scholarly journals Research on cutting performance and fatigue life of conical pick in cutting rock process

2021 ◽  
Vol 104 (4) ◽  
pp. 003685042110502
Author(s):  
Qingliang Zeng ◽  
Zhiwen Wang ◽  
Zhenguo Lu ◽  
Lirong Wan ◽  
Zhihai Liu ◽  
...  
Keyword(s):  
Fatigue Life ◽  
Cutting Force ◽  
Cutting Speed ◽  
Simulation Models ◽  
Cutting Parameters ◽  
Rock Damage ◽  
Specific Cutting Energy ◽  
Conical Pick ◽  
Research Results ◽  
Cutting Energy

The conical pick is the most crucial tool of roadheader for breaking rock, establishing the conical pick cutting rock and conical pick fatigue life numerical simulation models to investigate the influence of cutting parameters on rock damage, average peak cutting force, specific cutting energy and the conical pick fatigue life. The research results indicate that the width and depth of rock damage increase with increasing cutting depth and cutting speed. The average peak cutting force and the specific cutting energy have the same changing tendency. The changing trend of conical pick fatigue life and conical pick stress is opposite relationship. The optimum cutting angle of the conical pick cutting rock is 45°. Applying the research results for guiding the optimization of the cutting parameters reduces the specific cutting energy and stress and improves the conical pick fatigue life.

Modeling and Analysis of Cutting Forces in Hard Turning T250 Steel Using CBN Tools

2010 ◽  
Vol 154-155 ◽  
pp. 694-700
Author(s):  
Yue Ding ◽  
Xi Bin Wang ◽  
Li Jing Xie ◽  
Hao Yang
Keyword(s):  
Cutting Force ◽  
Analysis Of Variance ◽  
Feed Rate ◽  
Cutting Forces ◽  
Hard Turning ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Modeling And Analysis ◽  
Feed Force

The objective of this paper is to study the cutting forces in hard turning T250 steel with CBN tools. Experiments based on the Box-Behnken design were conducted to develop the cutting forces models by response surface methodology (RSM). Significance tests of the model are performed by the analysis of variance (ANOVA). It is also discussed the effects of cutting parameters (cutting speed, feed rate and depth of cut) on the cutting force components. The results show that the models can fit experimental data via analysis of variance. The most important cutting parameter is depth of cut, followed by feed rate, while the effect of cutting speed can be neglected. Compared to cutting force and feed force, thrust force is the largest. In addition, the cutting forces generated by the uncoated tool are smaller than by the coated one due to tool wear.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

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